1 files changed, 43 insertions, 65 deletions

diff --git a/tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp b/tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp
index 3abfb3c2ec..aec4d70271 100644
--- a/tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp
+++ b/tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp
@@ -4,9 +4,9 @@
 //
 
 #include "ModelAccuracyChecker.hpp"
-#include "../InferenceTest.hpp"
 #include "../ImagePreprocessor.hpp"
 #include "armnnDeserializer/IDeserializer.hpp"
+#include "../NetworkExecutionUtils/NetworkExecutionUtils.hpp"
 
 #include <boost/filesystem.hpp>
 #include <boost/range/iterator_range.hpp>
@@ -14,70 +14,8 @@
 
 using namespace armnn::test;
 
-namespace po = boost::program_options;
-
-bool CheckOption(const po::variables_map& vm,
-                 const char* option)
-{
-    // Check that the given option is valid.
-    if (option == nullptr)
-    {
-        return false;
-    }
-
-    // Check whether 'option' is provided.
-    return vm.find(option) != vm.end();
-}
-
-template<typename T, typename TParseElementFunc>
-std::vector<T> ParseArrayImpl(std::istream& stream, TParseElementFunc parseElementFunc, const char * chars = "\t ,:")
-{
-    std::vector<T> result;
-    // Processes line-by-line.
-    std::string line;
-    while (std::getline(stream, line))
-    {
-        std::vector<std::string> tokens;
-        try
-        {
-            // Coverity fix: boost::split() may throw an exception of type boost::bad_function_call.
-            boost::split(tokens, line, boost::algorithm::is_any_of(chars), boost::token_compress_on);
-        }
-        catch (const std::exception& e)
-        {
-            BOOST_LOG_TRIVIAL(error) << "An error occurred when splitting tokens: " << e.what();
-            continue;
-        }
-        for (const std::string& token : tokens)
-        {
-            if (!token.empty()) // See https://stackoverflow.com/questions/10437406/
-            {
-                try
-                {
-                    result.push_back(parseElementFunc(token));
-                }
-                catch (const std::exception&)
-                {
-                    BOOST_LOG_TRIVIAL(error) << "'" << token << "' is not a valid number. It has been ignored.";
-                }
-            }
-        }
-    }
-
-    return result;
-}
-
 map<std::string, int> LoadValidationLabels(const string & validationLabelPath);
 
-template<armnn::DataType NonQuantizedType>
-auto ParseDataArray(std::istream & stream);
-
-template<>
-auto ParseDataArray<armnn::DataType::Float32>(std::istream & stream)
-{
-    return ParseArrayImpl<float>(stream, [](const std::string& s) { return std::stof(s); });
-}
-
 int main(int argc, char* argv[])
 {
     try
@@ -94,6 +32,7 @@ int main(int argc, char* argv[])
         std::vector<armnn::BackendId> defaultBackends = {armnn::Compute::CpuAcc, armnn::Compute::CpuRef};
         std::string modelPath;
         std::string dataDir;
+        std::string inputType = "float";
         std::string inputName;
         std::string outputName;
         std::string validationLabelPath;
@@ -112,6 +51,9 @@ int main(int argc, char* argv[])
                  backendsMessage.c_str())
                 ("data-dir,d", po::value<std::string>(&dataDir)->required(),
                  "Path to directory containing the ImageNet test data")
+                ("input-type,y", po::value(&inputType), "The data type of the input tensors."
+                 "If unset, defaults to \"float\" for all defined inputs. "
+                 "Accepted values (float, int or qasymm8)")
                 ("input-name,i", po::value<std::string>(&inputName)->required(),
                  "Identifier of the input tensors in the network separated by comma.")
                 ("output-name,o", po::value<std::string>(&outputName)->required(),
@@ -217,14 +159,50 @@ int main(int argc, char* argv[])
 
         if(ValidateDirectory(dataDir))
         {
+            InferenceModel<armnnDeserializer::IDeserializer, float>::Params params;
+            params.m_ModelPath = modelPath;
+            params.m_IsModelBinary = true;
+            params.m_ComputeDevices = computeDevice;
+            params.m_InputBindings.push_back(inputName);
+            params.m_OutputBindings.push_back(outputName);
+
+            using TParser = armnnDeserializer::IDeserializer;
+            InferenceModel<TParser, float> model(params, false);
             for (auto & imageEntry : boost::make_iterator_range(directory_iterator(pathToDataDir), {}))
             {
                 cout << "Processing image: " << imageEntry << "\n";
 
                 std::ifstream inputTensorFile(imageEntry.path().string());
                 vector<TContainer> inputDataContainers;
-                inputDataContainers.push_back(ParseDataArray<armnn::DataType::Float32>(inputTensorFile));
-                vector<TContainer> outputDataContainers = {vector<float>(1001)};
+                vector<TContainer> outputDataContainers;
+
+                if (inputType.compare("float") == 0)
+                {
+                    inputDataContainers.push_back(
+                            ParseDataArray<armnn::DataType::Float32>(inputTensorFile));
+                    outputDataContainers = {vector<float>(1001)};
+                }
+                else if (inputType.compare("int") == 0)
+                {
+                    inputDataContainers.push_back(
+                            ParseDataArray<armnn::DataType::Signed32>(inputTensorFile));
+                    outputDataContainers = {vector<int>(1001)};
+                }
+                else if (inputType.compare("qasymm8") == 0)
+                {
+                    auto inputBinding = model.GetInputBindingInfo();
+                    inputDataContainers.push_back(
+                            ParseDataArray<armnn::DataType::QuantisedAsymm8>(
+                                    inputTensorFile,
+                                    inputBinding.second.GetQuantizationScale(),
+                                    inputBinding.second.GetQuantizationOffset()));
+                    outputDataContainers = {vector<uint8_t >(1001)};
+                }
+                else
+                {
+                    BOOST_LOG_TRIVIAL(fatal) << "Unsupported tensor data type \"" << inputType << "\". ";
+                    return EXIT_FAILURE;
+                }
 
                 status = runtime->EnqueueWorkload(networkId,
                                                   armnnUtils::MakeInputTensors(inputBindings, inputDataContainers),